Your purchase history and whether you use a mobile or desktop browser all can factor in large fluctuations in how much you pay.

Our experience on the web today is so personalized–our Google search results and Facebook News Feeds, our Amazon and Netflix suggestions. So it makes sense that online retailers would try to “personalize” prices they charge for products, too. Except that kind of deal doesn’t sound so great to most shoppers, especially when they don’t know if they’re the ones getting the short end of the stick.

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A new investigation conducted by researchers at Northeastern University provides a unique glimpse at how some online retailers engage in subtle price discrimination (charging different prices for the same product) and price “steering” (showing different search results that show products at higher or lower prices). Everything from whether a shopper was on a mobile or desktop browser to their history of clicks and purchases on the given e-commerce site seemed to have small effects.

“Ahead of time, we had no idea what we were going to find,” says study co-author Christo Wilson. “We thought that companies may be shying away from this. Turns out that’s not true.”

Travel websites, the researchers found, were the biggest offenders. For example, Travelocity charged mobile iOS users an average of $15 less than others. Orbitz and Cheaptickets charged people who weren’t logged onto the site an average of $12 more per night for hotel rooms. For other sites, like Expedia and Hotels.com, the researchers weren’t able to figure out the cause, but found that some people whose browsers contained specific cookies were guided to more expensive results than others. Priceline was found to alter hotel search results based on a user’s history of clicks and purchases on the site as tracked by browser cookies.

We thought that companies may be shying away from this. Turns out that’s not true.

Among the 10 general retailers surveyed such as Walmart, Staples, and JCPenney (this list did not include Amazon), only Home Depot steered mobile users to more expensive products, sometimes as much as roughly $80 more expensive. However, unlike with travel sites–where testers reserved hotel rooms but later canceled the reservations–the researchers did not generate “purchase histories” on the retailers’ sites to show how that might influence pricing.

The authors, who recruited 300 volunteers to browse the web and also created fake accounts to acts as controls, had to use an elaborate setup to conduct their research. It’s much harder than simply asking two people to shop on the same site at the same time, and seeing if they’re shown the same prices. They wanted to remove the effect of a shopper’s location (that’s already been shown to affect price) and account for other differences unrelated to personalization, such as which data servers process each search.

It’s ‘best match’ or ‘best for you.’ It’s totally opaque.

These pricing practices aren’t illegal, but unsurprisingly many people find them unfair because they aren’t transparent to shoppers, says Wilson. While anyone can go and get a coupon or see that a store offers, say, an AARP discount, we live in filter bubbles online. People generally don’t know what factors lead them to receiving the best deal online, and why retailers would want to offer different prices to desktop users and mobile users is really anyone’s guess.

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For people who really want to know that they’re getting the best deal, Wilson advises searching from a desktop while logged into the site, then again in a browser in “incognito” mode, then again from a smartphone, and for good measure, phoning a friend and having them search, too.

In the long-term, the research group wants to build tools that help people get around these practices by removing these kinds of tracking features. The conundrum is that while it’s easy to help obfuscate people, that’s not necessarily the tool that’s going to help people get the best prices.

“Perhaps that speaks to the need for regulation in this space,” says Wilson. “If you go to any site to search, very rarely are results first sorted by any objective metric. It’s ‘best match’ or ‘best for you.’ It’s totally opaque. And it’s fine if a company wants to do that, but they should explain what’s going on and how these decisions are being made.”